65 citations · 284 across the 13 of their papers we have counts for
13 papers
Advanced Virgo during the LIGO-Virgo-KAGRA fourth observing run
Virgo Collaboration, F Acernese, A Agapito +546
From April 10, 2024 to November 18, 2025 Advanced Virgo participated in the fourth observing run of the network of gravitational-wave detectors, together with Advanced LIGO and KAG…
Low- instabilities in differentially rotating neutron stars resembling merger remnants
Georgios Lioutas, Panagiotis Iosif, Andreas Bauswein +1
We construct constant rest-mass sequences of equilibrium models of differentially rotating neutron stars which resemble binary neutron star post-merger remnants. For a more realist…
Deep Residual Networks for Gravitational Wave Detection
Paraskevi Nousi, Alexandra E. Koloniari, Nikolaos Passalis +3
Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binari…
Virgo Detector Characterization and Data Quality: tools
F. Acernese, M. Agathos, A. Ain +491
Detector characterization and data quality studies -- collectively referred to as {\em DetChar} activities in this article -- are paramount to the scientific exploitation of the jo…
Virgo Detector Characterization and Data Quality: results from the O3 run
F. Acernese, M. Agathos, A. Ain +491
The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave (GW) signals in the past few years, alongside the two Adv…
MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge
Marlin B. Schäfer, Ondřej Zelenka, Alexander H. Nitz +20
We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitationa…
Virgo Detector Characterization and Data Quality during the O3 run
F. Acernese, M. Agathos, A. Ain +491
The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO ins…
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
Styliani-Christina Fragkouli, Paraskevi Nousi, Nikolaos Passalis +3
Deep learning methods have been employed in gravitational-wave astronomy to accelerate the construction of surrogate waveforms for the inspiral of spin-aligned black hole binaries,…
The Virgo O3 run and the impact of the environment
F. Acernese, M. Agathos, A. Ain +486
Sources of geophysical noise (such as wind, sea waves and earthquakes) or of anthropogenic noise impact ground-based gravitational-wave interferometric detectors, causing transient…
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Paraskevi Nousi, Styliani-Christina Fragkouli, Nikolaos Passalis +5
Recently, artificial neural networks have been gaining momentum in the field of gravitational wave astronomy, for example in surrogate modelling of computationally expensive wavefo…
Models of binary neutron star remnants with tabulated equations of state
Panagiotis Iosif, Nikolaos Stergioulas
The emergence of novel differential rotation laws that can reproduce the rotational profile of binary neutron star merger remnants has opened the way for the construction of equili…
Equilibrium sequences of differentially rotating stars with post-merger-like rotational profiles
Panagiotis Iosif, Nikolaos Stergioulas
We present equilibrium sequences of rotating relativistic stars, constructed with a new rotation law that was proposed by Uryu et al. (2017). We choose rotational parameters motiva…
On the accuracy of the IWM-CFC approximation in differentially rotating relativistic stars
Panagiotis Iosif, Nikolaos Stergioulas
We determine the accuracy of the conformal flatness (IWM-CFC) approximation for the case of single, but strongly differentially rotating relativistic stars. We find that for the fa…